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Found 9,737 Skills
Provides guidance for writing, packaging and executing Apache Beam pipelines on GCP using Cloud Dataflow. Use when: - Creating an Apache Beam Dataflow pipeline. - Creating a Google Flex Template.
Use these skills when you need to explore the database schema, identify objects like views and triggers, and execute custom SQL queries to interact with your data.
Process inbox in priority order by Spark's smart categories: priority first, then people, invites, notifications, newsletters.
Build a targeted contact segment by filtering on lifecycle, engagement, jobtitle, geography, or firmographics — then export it as JSONL for a campaign or downstream tool.
Identify which field values correlate with bad behavior (slowness, errors, anomalies, unusual values) using phi-coefficient correlation analysis over OPAL. Works on any time-series data — metrics, structured logs, span/trace data, or any dataset where rows can be split into a 'bad' and 'good' cohort by a threshold. Use when: (1) User asks for root-cause analysis on a dataset or metric (2) User wants to know what attributes / dimensions / values are most associated with a failure mode, anomaly, or unusual cohort (3) Investigating which services, hosts, regions, namespaces, or attributes drive outliers (4) User mentions phi coefficient, correlation, or outlier detection (5) User asks 'why is X slow/failing', 'what caused the errors on X', or 'what's different about the bad cohort'.
Self-contained deploy automation — invoke directly, do not decompose. Deploys Fireproof Connect to a dedicated Studio VM on exe.dev. Sets up cloud sync backend for all your Vibes apps.
Speak like a pirate.
Search the internet for real-time information, news, or facts using DuckDuckGo.
Use this skill during code reviews to proactively investigate the codebase for duplicated functionality, reinvented wheels, or failure to reuse existing project best practices and shared utilities.
Diagnose, compare, and optimize Apache Spark applications and SQL queries using Spark History Server data. Use this skill whenever the user wants to understand why a Spark app is slow, compare two benchmark runs or TPC-DS results, find performance bottlenecks (skew, GC pressure, shuffle spill, straggler tasks), get tuning recommendations, or optimize Spark/Gluten configurations. Also trigger when the user mentions 'diagnose', 'compare runs', 'why is this query slow', 'tune my Spark job', 'benchmark comparison', 'performance regression', or asks about executor skew, shuffle overhead, AQE effectiveness, or Gluten offloading issues.
Generate engaging, localized App Store release notes (What's New) from git log, bullet points, or free text using canonical metadata under `./metadata`. Optionally pairs with promotional text updates.
**STOP AND VERIFY**: Before running any command or tool that results in irreversible data loss, you MUST obtain explicit user consent. When in doubt, ask. It is better to wait for confirmation than to accidentally delete production data or critical project assets. Use this for: - SQL: DROP TABLE/VIEW/SCHEMA/DATABASE, TRUNCATE, or broad DELETE (missing WHERE or using 1=1). - Cloud Storage: gsutil rm or gcloud storage rm targeting production data or critical buckets. - Infrastructure: gcloud projects delete, deleting Spanner/BigQuery/Dataproc resources, deleting secrets, or KMS key destruction.